Makefile

.PHONY: setup download-data install test clean venv

VENV = .venv
PYTHON = $(VENV)/bin/python
PIP = $(VENV)/bin/pip

# Enhanced performance optimization env vars
export OMP_NUM_THREADS=8  # OpenMP threads 
export MKL_NUM_THREADS=8  # MKL threads
export NUMEXPR_NUM_THREADS=8  # NumExpr threads
export OPENBLAS_NUM_THREADS=8  # OpenBLAS threads
export TOKENIZERS_PARALLELISM=true  # Enable HuggingFace tokenizer parallelism
export TORCH_NUM_THREADS=8  # PyTorch threads
export CUDA_LAUNCH_BLOCKING=0  # Async CUDA operations
export PYTHONWARNINGS="ignore"  # Reduce overhead from warnings
export PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512  # Memory allocation strategy
export TRANSFORMERS_OFFLINE=1  # Avoid network checks
export HF_DATASETS_OFFLINE=1  # Avoid dataset downloads during processing

venv:
	python3 -m venv $(VENV)

setup: venv download-data install install-dashboard prepare-datasets
	$(PYTHON) -m spacy download en_core_web_sm

install-deps: venv
	$(PIP) install requests tqdm datasets transformers torch numpy sentencepiece protobuf \
		nltk spacy scikit-learn pandas scipy \
		beautifulsoup4 lxml textacy

download-data: install-deps
	$(PYTHON) -c "import nltk; nltk.download('punkt'); nltk.download('stopwords')"
	$(PYTHON) scripts/download_datasets.py

install: venv
	$(PIP) install -e .
	$(PIP) install spacy joblib pandas datasets transformers sentence-transformers tqdm torch numpy 
	$(PYTHON) -m spacy download en_core_web_sm

test: venv
	PYTHONPATH=. $(PYTHON) -m pytest tests/ -v --cov=src

format: venv
	$(PYTHON) -m black src/ tests/
	$(PYTHON) -m isort src/ tests/

lint: venv
	$(PYTHON) -m flake8 src/ tests/
	$(PYTHON) -m mypy src/ tests/

run-optimized: install-deps
	$(PYTHON) run_optimized.py --config config/config.yaml

run: venv
	$(PYTHON) run_optimized.py --config config/config.yaml

clean:
	rm -rf data/scisummnet.zip $(VENV)
	find . -type d -name "__pycache__" -exec rm -rf {} +
	find . -type d -name ".pytest_cache" -exec rm -rf {} +
	find . -type d -name ".mypy_cache" -exec rm -rf {} +

# Dashboard commands
run-dashboard:
	$(PYTHON) scripts/run_dashboard.py

install-dashboard:
	$(PIP) install dash dash-bootstrap-components plotly requests

test-api:
	$(PYTHON) -m pytest tests/test_arxiv_api.py -v

# Training commands
train-models:
	$(PYTHON) scripts/train_models.py

compare-models:
	$(PYTHON) scripts/compare_models.py

test-models:
	$(PYTHON) -m pytest tests/test_model_trainer.py -v

# Dataset preparation
prepare-datasets:
	$(PYTHON) scripts/prepare_datasets.py